Tapping Big Data Analytics to Acquire, Engage and Retain Customers

What it takes to fully leverage data for customer acquisition, engagement and retention.

According to a recent McKinsey Global Institute Report, marketing and sales consume about 15 percent of costs for bank and insurance customers. Recognizing that acquiring each new customer can cost hundreds of dollars, the most competitive financial services providers are turning to big data analytics to drive their customer acquisition, engagement and retention strategies in an effort to optimize their marketing spend.

These companies and their customers are generating massive amounts of data like purchase history, profile data, browsing history, product usage patterns and social media behavior every single day. Used wisely, this explosion in data can be harnessed to personalize marketing efforts tailored to customers’ interests, adjust product strategy based off of usage patterns and preemptively predict which customers are likely to leave. To successfully acquire, engage and retain customers, and ultimately gain a competitive advantage with big data analytics, financial services organizations should consider the following strategies:

Acquire: Combine Data Sources for More Targeted Promotions

With increasing access to valuable customer insights, financial institutions have the power to craft customized messages that will win new customers and help maintain a competitive edge.
Not only do organizations have access to traditional sources such as transactional history and profile demographics, but they also have access to public social media behavior. By combining these data sources, financial institutions have the ability to orchestrate more personalized and effective customer acquisition campaigns. For example, if a prospective customer made a number of purchases at Whole Foods and “liked” the Food Network on Facebook, a company could send a credit card with a special promotion related to Whole Foods or the Food Network.

Simply analyzing traditional customer data is no longer good enough. By analyzing traditional and emerging data sources together, companies can create campaigns around personalized promotions that are more effective and therefore lead to lower customer acquisition costs.

Engage: Iterate Product Offerings Based on Customer Usage Patterns

By looking inward to analyze customer usage data, companies can fine-tune product strategies and quickly deploy product improvements to keep customers engaged and satisfied. Historically, product management teams have spent a majority of their time managing reporting processes, rather than understanding how end-users interact with the product. To be competitive, they must employ data analysis solutions that allow them to quickly correlate changes in user traffic patterns and perform cohort analyses in the context of events such as new releases, A/B testing and outages to identify what is working and what is not. Armed with insights from the analysis, product management teams can focus on increasing value by accelerating new product models.

Retain: Reduce Customer Churn with Behavioral Analytics

Not only can big data analysis help financial institutions acquire new customers and engage current customers, but it can also mitigate attrition, and help retain customers who may be on the brink of leaving. If financial institutions can predict which customers are likely to transfer or withdraw their funds to a competitor, they are more likely to succeed at retaining them.

With big data analysis, organizations can track specific behaviors leading up to a transfer or withdrawal and preemptively identify and engage with the customer to address their outstanding concerns or needs. To do so, they need to track activities such as if a customer called in for information with an outside financial consultant on the line, a change in employment or power of attorney or if they recently browsed for information on the company site about transferring funds. By correlating this data, they can determine the statistical relevance of each activity or combination of activities that resulted in a withdrawal or transfer. By taking actions like offering relevant promotions, potentially changing interest rates, or other incentives based on the insights gained, companies can significantly increase the percentage of funds they retain that otherwise would have been transferred to a competitor.

Until recently, customer acquisition, engagement and retention strategies were mostly built based on historical information or gut instincts. To keep a competitive edge, financial institutions must leverage big data analytics to master these strategies. Once they harness the power of data and adopt a more proactive and personalized marketing strategy, the results will follow.